GE Renewable Energy has developed a new digital solution intended to increase hydropower plant efficiency using machine learning to pinpoint and monitor trouble spots.
Announced this week, GE Renewable Energy launched its new digital intelligent Condition Monitoring System (iCMS) for hydropower plants at the HydroVision Tradeshow being held in Minneapolis.
With the ever-increasing capacity of renewable energy technologies, GE Renewable Energy determined there was a need for hydropower plants to increase their flexibility and improve data assessment. As such, it developed iCMS, as a part of GE’s Asset Performance Management (APM) solution. Using machine learning to enhance the efficiency of monitoring and maintenance at hydropower plants, iCMS could theoretically generate an additional 1% of extra energy.
According to GE Renewable Energy, iCMS gathers and analyzes a variety of data in real time, including temperature, vibrations, acceleration, and rotational speed, and looks for early signs of mechanical or electrical problems which would not only cause inefficiencies in the hydropower plant, but also lead to long-term mechanical issues. The iCMS monitors and predicts a hydropower plant’s operations, enabling better fault and maintenance management.
iCMS is already in operation at Pont Baldy, a hydropower plant operated by Energie Développement Services du Briançonnais (EDSB) in the southeast of France, since December 2015. The results from Pont Baldy are amazing — iCMS has collected and analyzed almost 2 Terabytes of raw data per month, and internalized three years worth of previous temperature, maintenance, and downtime data.
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